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From the 1 of 6 linked papers with an AI index.

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6 papers

cs.SD2026

RFM-Editing 2: Text-Guided Audio Editing with Rectified Flow Matching and Coarse-to-Fine Diffusion Transformers

Liting Gao, Yonggang Zhu, Yaru Chen +5

The paper introduces RFM-Editing 2, a text‑guided audio editing system that uses rectified flow matching and a two‑stage diffusion transformer with a coarse‑to‑fine attention schem…

cs.SD2026

RFM-Editing: Rectified Flow Matching for Text-guided Audio Editing

Liting Gao, Yi Yuan, Yaru Chen +5

Diffusion models have shown remarkable progress in text-to-audio generation. However, text-guided audio editing remains in its early stages. This task focuses on modifying the targ…

cs.CV2025

TEn-CATG:Text-Enriched Audio-Visual Video Parsing with Multi-Scale Category-Aware Temporal Graph

Yaru Chen, Faegheh Sardari, Peiliang Zhang +4

Audio-visual video parsing (AVVP) aims to detect event categories and their temporal boundaries in videos, typically under weak supervision. Existing methods mainly focus on (i) im…

cs.CV2025

Teacher-Guided Pseudo Supervision and Cross-Modal Alignment for Audio-Visual Video Parsing

Yaru Chen, Ruohao Guo, Liting Gao +4

Weakly-supervised audio-visual video parsing (AVVP) seeks to detect audible, visible, and audio-visual events without temporal annotations. Previous work has emphasized refining gl…

cs.MM2025

TeMTG: Text-Enhanced Multi-Hop Temporal Graph Modeling for Audio-Visual Video Parsing

Yaru Chen, Peiliang Zhang, Fei Li +4

Audio-Visual Video Parsing (AVVP) task aims to parse the event categories and occurrence times from audio and visual modalities in a given video. Existing methods usually focus on…

cs.CV2025

Audio-Visual Instance Segmentation

Ruohao Guo, Xianghua Ying, Yaru Chen +11

In this paper, we propose a new multi-modal task, termed audio-visual instance segmentation (AVIS), which aims to simultaneously identify, segment and track individual sounding obj…